Sex differences across dimensions
Corrtraits and bifactor scores, ageInYears + sex01, n1601
## [1] "mood_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5535 -0.7318 0.0196 0.7053 3.7195
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.313557 0.134413 -9.773 <2e-16 ***
## ageInYears 0.088309 0.008314 10.622 <2e-16 ***
## sex011 0.131659 0.058142 2.264 0.0237 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9836 on 1150 degrees of freedom
## Multiple R-squared: 0.09428, Adjusted R-squared: 0.0927
## F-statistic: 59.85 on 2 and 1150 DF, p-value: < 2.2e-16
## [1] "psychosis_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.45813 -0.79866 -0.03699 0.73812 3.13767
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.963831 0.138116 -6.978 5.03e-12 ***
## ageInYears 0.072985 0.008543 8.543 < 2e-16 ***
## sex011 -0.029937 0.059744 -0.501 0.616
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.011 on 1150 degrees of freedom
## Multiple R-squared: 0.05971, Adjusted R-squared: 0.05808
## F-statistic: 36.51 on 2 and 1150 DF, p-value: 4.218e-16
## [1] "externalizing_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3548 -0.7263 0.0432 0.7114 3.2752
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.71261 0.13176 -5.408 7.74e-08 ***
## ageInYears 0.05613 0.00815 6.887 9.36e-12 ***
## sex011 -0.14888 0.05700 -2.612 0.00912 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9642 on 1150 degrees of freedom
## Multiple R-squared: 0.04414, Adjusted R-squared: 0.04247
## F-statistic: 26.55 on 2 and 1150 DF, p-value: 5.344e-12
## [1] "fear_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3742 -0.7782 -0.0345 0.7414 3.8793
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.88084 0.13984 -6.299 4.26e-10 ***
## ageInYears 0.05111 0.00865 5.909 4.52e-09 ***
## sex011 0.32687 0.06049 5.404 7.93e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.023 on 1150 degrees of freedom
## Multiple R-squared: 0.05455, Adjusted R-squared: 0.05291
## F-statistic: 33.18 on 2 and 1150 DF, p-value: 9.825e-15
## [1] "mood_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8635 -0.6903 -0.1013 0.6368 3.3181
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.998786 0.131395 -7.601 6.06e-14 ***
## ageInYears 0.053392 0.008127 6.569 7.64e-11 ***
## sex011 0.277439 0.056837 4.881 1.20e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9615 on 1150 degrees of freedom
## Multiple R-squared: 0.05678, Adjusted R-squared: 0.05514
## F-statistic: 34.61 on 2 and 1150 DF, p-value: 2.528e-15
## [1] "psychosis_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.4761 -0.4292 -0.2167 0.6212 3.1780
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.080893 0.141750 0.571 0.568
## ageInYears -0.004143 0.008768 -0.473 0.637
## sex011 0.036566 0.061316 0.596 0.551
##
## Residual standard error: 1.037 on 1150 degrees of freedom
## Multiple R-squared: 0.0004872, Adjusted R-squared: -0.001251
## F-statistic: 0.2803 on 2 and 1150 DF, p-value: 0.7556
## [1] "externalizing_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.71687 -0.71494 -0.08363 0.64046 3.03380
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.127334 0.131291 0.970 0.332
## ageInYears -0.003322 0.008121 -0.409 0.683
## sex011 -0.221973 0.056792 -3.909 9.83e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9608 on 1150 degrees of freedom
## Multiple R-squared: 0.01336, Adjusted R-squared: 0.01164
## F-statistic: 7.785 on 2 and 1150 DF, p-value: 0.0004383
## [1] "phobias_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.51793 -0.79343 -0.06447 0.72555 2.93788
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.231741 0.138647 -1.671 0.0949 .
## ageInYears -0.000956 0.008576 -0.111 0.9113
## sex011 0.456626 0.059974 7.614 5.53e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.015 on 1150 degrees of freedom
## Multiple R-squared: 0.04801, Adjusted R-squared: 0.04635
## F-statistic: 29 on 2 and 1150 DF, p-value: 5.185e-13
## [1] "overall_psychopathology_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.57466 -0.71366 0.01075 0.69323 2.86981
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.078088 0.136247 -7.913 5.88e-15 ***
## ageInYears 0.080220 0.008428 9.519 < 2e-16 ***
## sex011 -0.019894 0.058936 -0.338 0.736
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9971 on 1150 degrees of freedom
## Multiple R-squared: 0.07303, Adjusted R-squared: 0.07142
## F-statistic: 45.3 on 2 and 1150 DF, p-value: < 2.2e-16
Corrtraits and bifactor scores, ageInYears * sex01, n1601
## [1] "mood_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.6185 -0.7256 0.0101 0.7167 3.6474
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.99033 0.19027 -5.205 2.3e-07 ***
## ageInYears 0.06723 0.01210 5.558 3.4e-08 ***
## sex011 -0.48320 0.26318 -1.836 0.0666 .
## ageInYears:sex011 0.03982 0.01662 2.395 0.0168 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9816 on 1149 degrees of freedom
## Multiple R-squared: 0.09878, Adjusted R-squared: 0.09643
## F-statistic: 41.98 on 3 and 1149 DF, p-value: < 2.2e-16
## [1] "psychosis_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.38770 -0.79205 -0.04246 0.75903 3.16211
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.80961 0.19590 -4.133 3.84e-05 ***
## ageInYears 0.06293 0.01245 5.053 5.06e-07 ***
## sex011 -0.32330 0.27096 -1.193 0.233
## ageInYears:sex011 0.01900 0.01711 1.110 0.267
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.011 on 1149 degrees of freedom
## Multiple R-squared: 0.06072, Adjusted R-squared: 0.05827
## F-statistic: 24.76 on 3 and 1149 DF, p-value: 1.588e-15
## [1] "externalizing_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2000 -0.7332 0.0498 0.7137 3.2651
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.37359 0.18645 -2.004 0.04534 *
## ageInYears 0.03402 0.01185 2.870 0.00418 **
## sex011 -0.79378 0.25790 -3.078 0.00213 **
## ageInYears:sex011 0.04176 0.01629 2.564 0.01048 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9619 on 1149 degrees of freedom
## Multiple R-squared: 0.04957, Adjusted R-squared: 0.04709
## F-statistic: 19.98 on 3 and 1149 DF, p-value: 1.264e-12
## [1] "fear_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4459 -0.7617 -0.0308 0.7679 3.8204
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.61687 0.19814 -3.113 0.00190 **
## ageInYears 0.03390 0.01260 2.691 0.00723 **
## sex011 -0.17527 0.27406 -0.640 0.52261
## ageInYears:sex011 0.03252 0.01731 1.878 0.06058 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.022 on 1149 degrees of freedom
## Multiple R-squared: 0.05744, Adjusted R-squared: 0.05498
## F-statistic: 23.34 on 3 and 1149 DF, p-value: 1.142e-14
## [1] "mood_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.8108 -0.6666 -0.0651 0.6501 3.2275
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.59252 0.18570 -3.191 0.00146 **
## ageInYears 0.02689 0.01181 2.278 0.02291 *
## sex011 -0.49538 0.25685 -1.929 0.05402 .
## ageInYears:sex011 0.05005 0.01622 3.085 0.00209 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.958 on 1149 degrees of freedom
## Multiple R-squared: 0.06453, Adjusted R-squared: 0.06208
## F-statistic: 26.42 on 3 and 1149 DF, p-value: < 2.2e-16
## [1] "psychosis_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.4542 -0.4372 -0.2043 0.5995 3.2268
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.23562 0.20106 1.172 0.241
## ageInYears -0.01424 0.01278 -1.114 0.266
## sex011 -0.25777 0.27809 -0.927 0.354
## ageInYears:sex011 0.01906 0.01757 1.085 0.278
##
## Residual standard error: 1.037 on 1149 degrees of freedom
## Multiple R-squared: 0.00151, Adjusted R-squared: -0.001097
## F-statistic: 0.5794 on 3 and 1149 DF, p-value: 0.6286
## [1] "externalizing_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.68902 -0.70110 -0.07237 0.64748 3.03344
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.52086 0.18560 2.806 0.005094 **
## ageInYears -0.02899 0.01180 -2.457 0.014155 *
## sex011 -0.97057 0.25671 -3.781 0.000164 ***
## ageInYears:sex011 0.04848 0.01621 2.990 0.002852 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9575 on 1149 degrees of freedom
## Multiple R-squared: 0.02097, Adjusted R-squared: 0.01842
## F-statistic: 8.205 on 3 and 1149 DF, p-value: 2.095e-05
## [1] "phobias_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.52128 -0.81198 -0.05856 0.71866 2.93340
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.06616 0.19663 -0.336 0.737
## ageInYears -0.01176 0.01250 -0.940 0.347
## sex011 0.14165 0.27198 0.521 0.603
## ageInYears:sex011 0.02040 0.01718 1.187 0.235
##
## Residual standard error: 1.014 on 1149 degrees of freedom
## Multiple R-squared: 0.04917, Adjusted R-squared: 0.04669
## F-statistic: 19.81 on 3 and 1149 DF, p-value: 1.603e-12
## [1] "overall_psychopathology_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageInYears * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.51892 -0.70864 0.00061 0.69708 2.88915
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.95603 0.19328 -4.946 8.69e-07 ***
## ageInYears 0.07226 0.01229 5.881 5.35e-09 ***
## sex011 -0.25208 0.26734 -0.943 0.346
## ageInYears:sex011 0.01504 0.01689 0.890 0.373
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9971 on 1149 degrees of freedom
## Multiple R-squared: 0.07367, Adjusted R-squared: 0.07125
## F-statistic: 30.46 on 3 and 1149 DF, p-value: < 2.2e-16
Corrtraits and bifactor scores, ageInYears * sex01, n9498
## [1] "mood_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4675 -0.7004 -0.0251 0.6741 3.9668
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.2380640 0.0456565 -27.117 < 2e-16 ***
## ageAtClinicalAssess1 0.0066353 0.0002615 25.373 < 2e-16 ***
## sex011 0.1301900 0.0227173 5.731 1.04e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9486 on 7050 degrees of freedom
## Multiple R-squared: 0.09165, Adjusted R-squared: 0.09139
## F-statistic: 355.7 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "psychosis_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2046 -0.7499 -0.1041 0.7223 3.4561
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.9512454 0.0467147 -20.363 <2e-16 ***
## ageAtClinicalAssess1 0.0054907 0.0002676 20.521 <2e-16 ***
## sex011 -0.0456210 0.0232438 -1.963 0.0497 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9706 on 7050 degrees of freedom
## Multiple R-squared: 0.05636, Adjusted R-squared: 0.0561
## F-statistic: 210.5 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "externalizing_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1410 -0.8297 0.0205 0.7255 3.3760
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.5147003 0.0476978 -10.791 <2e-16 ***
## ageAtClinicalAssess1 0.0034643 0.0002732 12.680 <2e-16 ***
## sex011 -0.2015553 0.0237330 -8.493 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.991 on 7050 degrees of freedom
## Multiple R-squared: 0.02948, Adjusted R-squared: 0.0292
## F-statistic: 107.1 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "fear_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3991 -0.7497 -0.0047 0.6802 4.0515
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.8781442 0.0469267 -18.71 <2e-16 ***
## ageAtClinicalAssess1 0.0041948 0.0002688 15.61 <2e-16 ***
## sex011 0.2634741 0.0233493 11.28 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.975 on 7050 degrees of freedom
## Multiple R-squared: 0.05479, Adjusted R-squared: 0.05453
## F-statistic: 204.3 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "mood_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.9518 -0.7055 -0.0991 0.6475 4.4043
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.7741032 0.0460228 -16.82 <2e-16 ***
## ageAtClinicalAssess1 0.0034109 0.0002636 12.94 <2e-16 ***
## sex011 0.3106466 0.0228995 13.57 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9562 on 7050 degrees of freedom
## Multiple R-squared: 0.05229, Adjusted R-squared: 0.05202
## F-statistic: 194.5 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "psychosis_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.4456 -0.3629 -0.1825 0.4410 4.5461
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0065255 0.0472896 0.138 0.890
## ageAtClinicalAssess1 -0.0001371 0.0002709 -0.506 0.613
## sex011 0.0025211 0.0235298 0.107 0.915
##
## Residual standard error: 0.9825 on 7050 degrees of freedom
## Multiple R-squared: 3.683e-05, Adjusted R-squared: -0.0002468
## F-statistic: 0.1298 on 2 and 7050 DF, p-value: 0.8783
## [1] "externalizing_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7463 -0.7748 -0.1043 0.6864 3.5817
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.3891417 0.0477328 8.153 4.18e-16 ***
## ageAtClinicalAssess1 -0.0014714 0.0002734 -5.382 7.61e-08 ***
## sex011 -0.2911400 0.0237504 -12.258 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9917 on 7050 degrees of freedom
## Multiple R-squared: 0.02675, Adjusted R-squared: 0.02647
## F-statistic: 96.89 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "phobias_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5985 -0.7591 -0.0831 0.7052 4.5401
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.2585893 0.0471152 -5.488 4.2e-08 ***
## ageAtClinicalAssess1 0.0004535 0.0002699 1.681 0.0929 .
## sex011 0.3442835 0.0234431 14.686 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9789 on 7050 degrees of freedom
## Multiple R-squared: 0.03098, Adjusted R-squared: 0.0307
## F-statistic: 112.7 on 2 and 7050 DF, p-value: < 2.2e-16
## [1] "overall_psychopathology_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 + sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3589 -0.7216 -0.0415 0.6842 3.1760
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.0856088 0.0464185 -23.387 <2e-16 ***
## ageAtClinicalAssess1 0.0062406 0.0002659 23.472 <2e-16 ***
## sex011 -0.0209238 0.0230964 -0.906 0.365
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9644 on 7050 degrees of freedom
## Multiple R-squared: 0.07271, Adjusted R-squared: 0.07245
## F-statistic: 276.4 on 2 and 7050 DF, p-value: < 2.2e-16
Corrtraits and bifactor scores, ageInYears * sex01, n9498
## [1] "mood_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5318 -0.7058 -0.0193 0.6718 3.9244
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.0394061 0.0639614 -16.251 < 2e-16 ***
## ageAtClinicalAssess1 0.0054169 0.0003793 14.280 < 2e-16 ***
## sex011 -0.2566989 0.0902550 -2.844 0.00447 **
## ageAtClinicalAssess1:sex011 0.0023164 0.0005230 4.429 9.62e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9474 on 7049 degrees of freedom
## Multiple R-squared: 0.09417, Adjusted R-squared: 0.09379
## F-statistic: 244.3 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "psychosis_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2282 -0.7465 -0.1008 0.7226 3.4356
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.0038099 0.0655288 -15.319 <2e-16 ***
## ageAtClinicalAssess1 0.0058131 0.0003886 14.958 <2e-16 ***
## sex011 0.0567489 0.0924666 0.614 0.539
## ageAtClinicalAssess1:sex011 -0.0006129 0.0005359 -1.144 0.253
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9706 on 7049 degrees of freedom
## Multiple R-squared: 0.05654, Adjusted R-squared: 0.05614
## F-statistic: 140.8 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "externalizing_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.0619 -0.8136 0.0246 0.7253 3.3779
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.3534375 0.0668579 -5.286 1.28e-07 ***
## ageAtClinicalAssess1 0.0024752 0.0003965 6.242 4.56e-10 ***
## sex011 -0.5156169 0.0943422 -5.465 4.78e-08 ***
## ageAtClinicalAssess1:sex011 0.0018804 0.0005467 3.439 0.000586 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9903 on 7049 degrees of freedom
## Multiple R-squared: 0.0311, Adjusted R-squared: 0.03069
## F-statistic: 75.43 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "fear_corrtraitsv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.4418 -0.7495 -0.0075 0.6835 4.0201
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.7311084 0.0657848 -11.114 < 2e-16 ***
## ageAtClinicalAssess1 0.0032930 0.0003901 8.440 < 2e-16 ***
## sex011 -0.0228800 0.0928279 -0.246 0.80532
## ageAtClinicalAssess1:sex011 0.0017145 0.0005379 3.187 0.00144 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9744 on 7049 degrees of freedom
## Multiple R-squared: 0.05615, Adjusted R-squared: 0.05575
## F-statistic: 139.8 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "mood_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.9189 -0.6866 -0.0895 0.6374 4.2898
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.2958243 0.0640510 -4.619 3.93e-06 ***
## ageAtClinicalAssess1 0.0004775 0.0003799 1.257 0.209
## sex011 -0.6208079 0.0903815 -6.869 7.03e-12 ***
## ageAtClinicalAssess1:sex011 0.0055770 0.0005238 10.648 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9487 on 7049 degrees of freedom
## Multiple R-squared: 0.06729, Adjusted R-squared: 0.06689
## F-statistic: 169.5 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "psychosis_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.4708 -0.3620 -0.1803 0.4418 4.5598
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0828778 0.0663239 -1.250 0.2115
## ageAtClinicalAssess1 0.0004112 0.0003933 1.045 0.2958
## sex011 0.1766352 0.0935887 1.887 0.0592 .
## ageAtClinicalAssess1:sex011 -0.0010425 0.0005424 -1.922 0.0546 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9823 on 7049 degrees of freedom
## Multiple R-squared: 0.0005607, Adjusted R-squared: 0.0001353
## F-statistic: 1.318 on 3 and 7049 DF, p-value: 0.2665
## [1] "externalizing_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.7717 -0.7678 -0.1080 0.6774 3.5609
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.6311940 0.0668367 9.444 < 2e-16 ***
## ageAtClinicalAssess1 -0.0029560 0.0003964 -7.457 9.88e-14 ***
## sex011 -0.7625401 0.0943123 -8.085 7.24e-16 ***
## ageAtClinicalAssess1:sex011 0.0028224 0.0005466 5.164 2.48e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9899 on 7049 degrees of freedom
## Multiple R-squared: 0.03042, Adjusted R-squared: 0.03001
## F-statistic: 73.72 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "phobias_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5794 -0.7609 -0.0816 0.7061 4.5050
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0904629 0.0660350 -1.370 0.170754
## ageAtClinicalAssess1 -0.0005776 0.0003916 -1.475 0.140274
## sex011 0.0168551 0.0931809 0.181 0.856462
## ageAtClinicalAssess1:sex011 0.0019604 0.0005400 3.630 0.000285 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9781 on 7049 degrees of freedom
## Multiple R-squared: 0.03278, Adjusted R-squared: 0.03237
## F-statistic: 79.64 on 3 and 7049 DF, p-value: < 2.2e-16
## [1] "overall_psychopathology_4factorv2"
##
## Call:
## lm(formula = yvar ~ ageAtClinicalAssess1 * sex01, data = newdata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.3464 -0.7185 -0.0419 0.6814 3.1636
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.1172707 0.0651170 -17.158 <2e-16 ***
## ageAtClinicalAssess1 0.0064348 0.0003862 16.662 <2e-16 ***
## sex011 0.0407382 0.0918856 0.443 0.658
## ageAtClinicalAssess1:sex011 -0.0003692 0.0005325 -0.693 0.488
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9645 on 7049 degrees of freedom
## Multiple R-squared: 0.07277, Adjusted R-squared: 0.07238
## F-statistic: 184.4 on 3 and 7049 DF, p-value: < 2.2e-16